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Senior Machine Learning Engineer(m/w/x)
Architecting multifaceted search engines and aggregating data from multiple sources for a DaaS company. 5+ years production ML engineering experience required. Up to 4 weeks working abroad per year.
Requirements
- Master's degree in Computer Science, Engineering, Statistics, or related STEM field
- 5+ years hands-on ML Engineer experience in production
- Expert-level Python skills
- Strong SQL proficiency
- Proven NLP models development and deployment experience
- Proven information retrieval systems development and deployment experience
- Proven search engines development and deployment experience
- Hands-on AI and LLMs integration into ML pipelines experience
- Strong software engineering best practices foundation
- Focus on clean, maintainable, scalable code
- Proven scalable, production-grade ML systems design and delivery
- Proven scalable, production-grade ML architectures design and delivery
- Cloud platforms working experience
- CI/CD workflows working experience
- Containerized environments working experience
- Experience leading technical initiatives
- High degree of ownership and accountability
- Strong mentoring skills
- Ability to support junior team members
- Ability to guide junior team members
- Proactive mindset
- Ability to take ownership
- Ability to drive solutions forward
- Ability to navigate ambiguity
- Strong analytical thinking
- Structured problem-solving skills
- Highly efficient execution
- Excellent communication skills
- English fluency
- Experience in low-code languages like C++
- Experience in low-code languages like Java
- AWS working experience
- SageMaker working experience
- Prior LLMs fine-tuning experience
- Prior LLMs training experience
- Practical data pipelines building experience
- Practical data pipelines managing experience
Tasks
- Design and implement advanced ML features
- Take end-to-end ownership of ML projects
- Architect multifaceted search engines
- Aggregate and retrieve data from multiple sources
- Design scalable system architectures
- Drive technical decisions for long-term maintainability
- Develop and maintain microservices
- Integrate microservices into larger applications
- Apply and guide adoption of latest ML advancements
- Train and optimize models for performance
- Evaluate models for scalability and reliability
- Mentor and support other ML engineers
- Foster a collaborative engineering culture
- Collaborate with ML engineers and backend engineers
- Work closely with product owners
- Lead cross-functional initiatives
- Contribute to a balanced tech stack
- Prioritize simplicity and maintainability
- Ensure high-quality code through code reviews
- Follow engineering best practices
- Participate in Agile/Scrum processes
- Share insights and feedback
Work Experience
- 5 years
Education
- Master's degree
Languages
- English – Fluent
Tools & Technologies
- Python
- SQL
- NLP
- AI
- LLMs
- AWS
- SageMaker
- C++
- Java
Benefits
Flexible Working
- Flexible working hours
- Hybrid model
- Home office days
Workation & Sabbatical
- Up to 4 weeks working abroad per year
Learning & Development
- Paid training days
Purpose-Driven Work
- Paid volunteering days
Social Impact
- Charity donation matching
Healthcare & Fitness
- Health & fitness subsidy
Team Events
- Frequent team and social events
Snacks & Drinks
- Complimentary coffee
- Complimentary refreshments
- Complimentary fresh fruit
- Complimentary healthy snacks
Informal Culture
- Welcoming office environment
Other Benefits
- Diversity and inclusion
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Senior Machine Learning Engineer(m/w/x)
Architecting multifaceted search engines and aggregating data from multiple sources for a DaaS company. 5+ years production ML engineering experience required. Up to 4 weeks working abroad per year.
Requirements
- Master's degree in Computer Science, Engineering, Statistics, or related STEM field
- 5+ years hands-on ML Engineer experience in production
- Expert-level Python skills
- Strong SQL proficiency
- Proven NLP models development and deployment experience
- Proven information retrieval systems development and deployment experience
- Proven search engines development and deployment experience
- Hands-on AI and LLMs integration into ML pipelines experience
- Strong software engineering best practices foundation
- Focus on clean, maintainable, scalable code
- Proven scalable, production-grade ML systems design and delivery
- Proven scalable, production-grade ML architectures design and delivery
- Cloud platforms working experience
- CI/CD workflows working experience
- Containerized environments working experience
- Experience leading technical initiatives
- High degree of ownership and accountability
- Strong mentoring skills
- Ability to support junior team members
- Ability to guide junior team members
- Proactive mindset
- Ability to take ownership
- Ability to drive solutions forward
- Ability to navigate ambiguity
- Strong analytical thinking
- Structured problem-solving skills
- Highly efficient execution
- Excellent communication skills
- English fluency
- Experience in low-code languages like C++
- Experience in low-code languages like Java
- AWS working experience
- SageMaker working experience
- Prior LLMs fine-tuning experience
- Prior LLMs training experience
- Practical data pipelines building experience
- Practical data pipelines managing experience
Tasks
- Design and implement advanced ML features
- Take end-to-end ownership of ML projects
- Architect multifaceted search engines
- Aggregate and retrieve data from multiple sources
- Design scalable system architectures
- Drive technical decisions for long-term maintainability
- Develop and maintain microservices
- Integrate microservices into larger applications
- Apply and guide adoption of latest ML advancements
- Train and optimize models for performance
- Evaluate models for scalability and reliability
- Mentor and support other ML engineers
- Foster a collaborative engineering culture
- Collaborate with ML engineers and backend engineers
- Work closely with product owners
- Lead cross-functional initiatives
- Contribute to a balanced tech stack
- Prioritize simplicity and maintainability
- Ensure high-quality code through code reviews
- Follow engineering best practices
- Participate in Agile/Scrum processes
- Share insights and feedback
Work Experience
- 5 years
Education
- Master's degree
Languages
- English – Fluent
Tools & Technologies
- Python
- SQL
- NLP
- AI
- LLMs
- AWS
- SageMaker
- C++
- Java
Benefits
Flexible Working
- Flexible working hours
- Hybrid model
- Home office days
Workation & Sabbatical
- Up to 4 weeks working abroad per year
Learning & Development
- Paid training days
Purpose-Driven Work
- Paid volunteering days
Social Impact
- Charity donation matching
Healthcare & Fitness
- Health & fitness subsidy
Team Events
- Frequent team and social events
Snacks & Drinks
- Complimentary coffee
- Complimentary refreshments
- Complimentary fresh fruit
- Complimentary healthy snacks
Informal Culture
- Welcoming office environment
Other Benefits
- Diversity and inclusion
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
RepRisk AG
Industry
FinancialServices
Description
RepRisk is the world’s most respected Data as a Service (DaaS) company for reputational risks and responsible business conduct.
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